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Modeling of HIV/AIDS dynamic evolution using non-homogeneous semi-markov process
1Department of Statistics, College of Science, Bahir Dar University, Bahir Dar, Ethiopia.
This study models HIV/AIDS progression using age and CD4 counts, finding older patients and lower counts increase mortality risk. Interventions are crucial as patients tend towards worse health states without them.
Area of Science:
- Epidemiology
- Biostatistics
- Public Health
Background:
- HIV/AIDS remains a significant global health challenge.
- Antiretroviral Therapy (ART) has transformed HIV management.
- Understanding disease progression dynamics is crucial for effective patient care.
Purpose of the Study:
- To model HIV/AIDS disease progression in patients under ART.
- To investigate the influence of patient age on disease transitions.
- To utilize non-homogeneous semi-Markov processes for forecasting.
Main Methods:
- A cohort of 1456 HIV/AIDS patients under ART follow-up in Ethiopia was analyzed.
- Disease states were defined by CD4 cell counts: SI (>500), SII (349-500), SIII (199-350), SIV (≤200), and Death (D).
- Non-homogeneous semi-Markov processes were employed to model transitions, incorporating age as a covariate.
Main Results:
- Increasing age significantly elevates the probability of transitioning to the death state.
- Higher CD4 cell counts correlate with a decreased probability of mortality.
- The likelihood of remaining in the same disease state diminishes with advancing age.
- Patients are more prone to progressing to worse health states than improving, highlighting the need for interventions.
Conclusions:
- Age is a critical factor influencing HIV/AIDS progression and mortality risk.
- ART effectiveness can be enhanced by considering individual patient age and current disease status.
- Dynamic monitoring and timely interventions are essential for managing HIV/AIDS progression effectively.
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